code: def __init__(
      self, inplanes, planes, stride=1, downsample=None, reduction=8
  ):
      super(SEBasicBlock, self).__init__()
      self.conv1 = nn.Conv2d(
          inplanes,
          planes,
          kernel_size=3,
          stride=stride,
          padding=1,
          bias=False,
      )
      self.bn1 = nn.BatchNorm2d(planes)
      self.conv2 = nn.Conv2d(
          planes, planes, kernel_size=3, padding=1, bias=False
      )
      self.bn2 = nn.BatchNorm2d(planes)
      self.relu = nn.ReLU(inplace=True)
      self.se = SELayer(planes, reduction)
      self.downsample = downsample
      self.stride = stride
  
file_path: TTS/TTS/encoder/models/resnet.py
imports: import torch
  from torch import nn
  from TTS.encoder.models.base_encoder import BaseEncoder
label_desc: Use image node_id 1 to create a new SEBasicBlock object from inherited base classes: nn with example: obj = SEBasicBlock(inplanes, planes, stride, downsample, reduction)